Deep learning (DL) has recently emerged as a pivotal technology for enhancing magnetic resonance imaging (MRI), a critical tool in diagnostic radiology. This review paper provides a comprehensive overview of recent advances in DL for MRI reconstructi...
Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Jul 23, 2024
PURPOSE: To investigate the potential phases in myopic retinal vascular alterations for further elucidating the mechanisms underlying the progression of high myopia (HM).
BACKGROUND: Preoperative assessment of the impacted mandibular third molar (LM3) in a panoramic radiograph is important in surgical planning. The aim of this study was to develop and evaluate a computer-aided visualisation-based deep learning (DL) sy...
Journal of imaging informatics in medicine
Jul 22, 2024
Adenomatous polyps, a common premalignant lesion, are often classified into villous adenoma (VA) and tubular adenoma (TA). VA has a higher risk of malignancy, whereas TA typically grows slowly and has a lower likelihood of cancerous transformation. A...
RATIONALE AND OBJECTIVES: Perineural invasion (PNI) is an important prognostic biomarker for prostate cancer (PCa). This study aimed to develop and validate a predictive model integrating biparametric MRI-based deep learning radiomics and clinical ch...
Neural networks : the official journal of the International Neural Network Society
Jul 22, 2024
Lossy image coding techniques usually result in various undesirable compression artifacts. Recently, deep convolutional neural networks have seen encouraging advances in compression artifact reduction. However, most of them focus on the restoration o...
PURPOSE: The purpose of this study is to develop and apply an algorithm that automatically classifies spine radiographs of pediatric scoliosis patients.
OBJECTIVES: Fetal cleft lip is a common congenital defect. Considering the delicacy and difficulty of observing fetal lips, we have utilized deep learning technology to develop a new model aimed at quickly and accurately assessing the development of ...
Behavioural thermoregulation has critical ecological and physiological consequences that profoundly influence individual fitness and species distributions, particularly in the context of climate change. However, field monitoring of this behaviour rem...
BACKGROUND: Convolutional neural network (CNN) can capture the structural features changes of brain aging based on MRI, thus predict brain age in healthy individuals accurately. However, most studies use single feature to predict brain age in healthy...
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